CVE-2026-120335
Received Received - Intake

Path Traversal in deepset-ai farm Model Package Loader

Publication date: 2026-11-02

Last updated on: 2026-11-02

Assigner: VulDB

Description
A vulnerability has been found in deepset-ai farm up to 0.8.0. Affected is the function WordEmbedding_LM.load of the file farm/modeling/language_model.py of the component Model Package Loader. The manipulation of the argument embeddings_filename leads to path traversal. An attack has to be approached locally. The exploit has been disclosed to the public and may be used. The vendor was contacted early about this disclosure but did not respond in any way. This vulnerability only affects products that are no longer supported by the maintainer.

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Meta Information

Published
2026-11-02
Last Modified
2026-11-02
Generated
2026-11-02
AI Q&A
2026-11-02
EPSS Evaluated
N/A
NVD
CVE-2026-120335

Affected Vendors & Products

Helpful Resources

Exploitability

CWE
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KEV
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CWE ID Description
CWE-22 The product uses external input to construct a pathname that is intended to identify a file or directory that is located underneath a restricted parent directory, but the product does not properly neutralize special elements within the pathname that can cause the pathname to resolve to a location that is outside of the restricted directory.

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Executive Summary

This vulnerability is a path traversal issue in the deepset-ai FARM library up to version 0.8.0. It occurs in the WordEmbedding_LM.load function where the embeddings_filename argument can be manipulated to access files outside the intended directory. For example, an attacker could use a relative path like ../victim_private/vectors.txt to read sensitive files.

Detection Guidance

Check for suspicious model packages with relative paths in embeddings_filename. Inspect language_model_config.json files for entries like ../ or absolute paths. Monitor for unexpected file access in model directories.

Impact Analysis

This vulnerability allows an attacker to access arbitrary files on your system if you use a vulnerable version of FARM. This could lead to disclosure of confidential data or manipulation of model weights by loading malicious files. The attack requires local access but can be executed by tricking a user into loading a specially crafted model package.

Compliance Impact

This vulnerability could lead to violations of GDPR and HIPAA by enabling unauthorized access to sensitive data. GDPR requires protection of personal data, while HIPAA mandates safeguards for protected health information. A breach through this vulnerability could result in legal penalties and reputational damage.

Mitigation Strategies

Stop using untrusted model packages. Implement path validation using os.path.realpath() before loading. Sandbox model loading in isolated environments. Migrate to actively maintained alternatives.

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